The project “Energy-efficient health and behavior monitoring with wearable devices and the Internet of Things” (FEATURE) is funded under the activity 188.8.131.52 “Post-doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Programme “Growth and Employment”. The project is implemented with the support of the European Regional Development Fund (ERDF).
Contract number with the State Education Development Agency (SEDA): nr. 9.-14.5/86
The manager and the responsible researcher of the project is Dr. Atis Elsts.
The objective of FEATURE is to increase the energy efficiency of health and health-related behavior monitoring with wearable devices and other wirelessly interconnected, computationally-constrained Internet of Things (IoT) sensor devices. The project focuses on using machine learning and IoT techniques for health and behavior monitoring.
Project duration: December 1, 2018 – November 30, 2021.
Total funding: 133 805.88 EUR, from which ERDF funding 113 734.99 EUR, state budget funding 13 380.58 EUR and base funding from EDI 6 690.31 EUR.
July 23, 2020. The article “Energy-efficient activity recognition framework using wearable accelerometers” is available in the online version of Elsevier Journal of Network and Computer Applications https://doi.org/10.1016/j.jnca.2020.102770
March 13, 2020. The article “From Bits of Data to Bits of Knowledge: An On-Board Classification Framework for Wearable Sensing Systems” is accepted for publication in the journal MDPI Sensors.
March 6, 2020. The article “An Empirical Survey of Autonomous Scheduling Methods for TSCH” is accepted for publication in the journal IEEE Access.
February 17, 2020. In the conference’s EWSN workshop OBSN A. Vafeas presents the project-supported publication “Wearable Devices for Digital Health: The SPHERE Wearable 3”. Program: https://ubicomp.eti.uni-siegen.de/workshop/obsn2020/
October 16, 2019. The paper “TSCH Networks for Health IoT: Design, Evaluation and Trials in the Wild” has been accepted for publication, in the journal ACM Transactions on the Internet of Things. Authors: A. Elsts, X. Fafoutis, G. Oikonomou, R. Piechocki and I. Craddock.
August 18-31, 2019. Atis Elsts is visiting Bristol (UK) for an internship at the University of Bristol and experiments with energy efficient wearable systems and network communication with the University of Bristol’s Digital Health Engineering team.
May 28-29, 2019. Atis Elsts is on a business trip to Zurich (Switzerland) to visit Miromico AG and present it to the FEATURE project’s research on mobile devices in IEEE 802.15.4 TSCH networks, as well as to discuss future collaboration opportunities.
May 2, 2019. Atis Elsts talks about his post-doctoral research project “Energy-efficient monitoring of health status and behavior with wearable devices and the Internet of Things” on the LTV channel at 19:30 in the program “Cognitive Impulse”. https://www.lsm.lv/raksts/dzive–stils/tehnologijas-un-zinatne/programmetajs-atis-elsts-pilnveido-valkajamas-ierices-cilveku-veselibas-uzlabosanai.a318540/
February 23-28, 2019. Atis Elsts is visiting Tsinghua University, Beijing, China to attend the International Conference on Embedded Wireless Systems and Networks (EWSN 2019) and present an article entitled “Instant: A TSCH Schedule for Data Collection from Mobile Nodes ”.
February 14, 2019. 10:00 A seminar is being held at the Institute of Electronics and Computer Science, Auditorium A, where Atis Elsts talks about his experience on a mobility visit to the University of Bristol.
January 31, 2019. 11:00 A seminar from the Digital Health Engineering Group is taking place at the University of Bristol, where Atis Elsts will give a presentation on “The New Generation SPHERE Wearable: Overview and Research Perspectives”.
December 9, 2018 – February 9, 2019. Atis Elsts is in a mobility visit at the University of Bristol. Experience is being supplemented and joint work is being done on the hardware and software required to achieve the project objectives, as well as the publication “Accuracy-Energy Trade-Off in Feature Selection for Activity Recognition using Wearable Accelerometers”.
SPHERE Wearable 3 (University of Bristol) used in the FEATURE project.